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Computational Methods in Decision-Making, Economics and Finance
Erricos John Kontoghiorghes
B. Rustem
S. Siokos
出版
Springer Science & Business Media
, 2002-08-31
主題
Business & Economics / General
Business & Economics / Decision-Making & Problem Solving
Business & Economics / Entrepreneurship
Business & Economics / Finance / General
Business & Economics / Finance / Financial Engineering
Business & Economics / Investments & Securities / General
Business & Economics / Investments & Securities / Portfolio Management
Business & Economics / Management Science
Business & Economics / Operations Research
Business & Economics / Economics / General
Business & Economics / Information Management
Business & Economics / Business Mathematics
Computers / Computer Architecture
Computers / Information Technology
Computers / Management Information Systems
Computers / Programming / Algorithms
Mathematics / Applied
Mathematics / Linear & Nonlinear Programming
Mathematics / Numerical Analysis
Mathematics / Optimization
Medical / General
ISBN
1402008392
9781402008399
URL
http://books.google.com.hk/books?id=YC-noNAEPT0C&hl=&source=gbs_api
EBook
SAMPLE
註釋
Computing has become essential for the modeling, analysis, and optimization of systems. This book is devoted to algorithms, computational analysis, and decision models. The chapters are organized in two parts: optimization models of decisions and models of pricing and equilibria.
Optimization is at the core of rational decision making. Even when the decision maker has more than one goal or there is significant uncertainty in the system, optimization provides a rational framework for efficient decisions. The Markowitz mean-variance formulation is a classical example. The first part of the book is on recent developments in optimization decision models for finance and economics. The first four chapters of this part focus directly on multi-stage problems in finance. Chapters 5-8 involve the use of worst-case robust analysis. Chapters 9-11 are devoted to portfolio optimization. The final four chapters are on transportation-inventory with stochastic demand; optimal investment with CRRA utility; hedging financial contracts; and, automatic differentiation for computational finance.
The uncertainty associated with prediction and modeling constantly requires the development of improved methods and models. Similarly, as systems strive towards equilibria, the characterization and computation of equilibria assists analysis and prediction. The second part of the book is devoted to recent research in computational tools and models of equilibria, prediction, and pricing. The first three chapters of this part consider hedging issues in finance. Chapters 19-22 consider prediction and modeling methodologies. Chapters 23-26 focus on auctions and equilibria. Volatility models are investigated in chapters 27-28. The final two chapters investigate risk assessment and product pricing.
Audience: Researchers working in computational issues related to economics, finance, and management science.